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Feebates – Modeling

DEVELOPMENT OF OPTIONS FOR A VEHICLE FEEBATE IN CANADA

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4. MODELING OF FEEBATE OPTIONS

4.1 DESCRIPTION OF MODELS

separate models were used in this analysis:

• TransportCanada Variant of Greene et al. Vehicle Purchase Model. 

  This is a spreadsheet-based, nested multinomial logit,consumer choice model that estimates the effect of

  feebates on consumer purchasing behaviour and manufacturer

  investment in fuel economy technologies. Each individual

  vehicle model is included (830 in total North American

  market), as well as its purchase price and fuel economy.

  The model solves for fuel economy changes that maximize

  consumer surplus given a defined feebate. Consumer

  surplus is maximized in response to the feebate “price”

  by:

  • shiftingvehicle demand towards more fuel-efficient carsand reducing overall vehicle demand
  • inducingmanufacturers to maintain or improve market shareby improving fuel economy, and
  • providingfuel savings to the consumer through lower overallfuel consumption.
  The

  model produces aggregate national results for a

  single future year (15 years in the future), representing

  the new long-run equilibrium impact of the feebate.

  Transport Canada modified the US model to use aggregated

  2003 Canadian and US sales data, updated the technology

  cost curves based on a 2005 literature review (necessary

  to track manufacturer responses to the feebate),

  and added redesign thresholds provided by EEA. (These

  EEA redesign thresholds are used to determine if

  sales are adequate in Canada to induce manufacturers

  to make manufacturing investments that produce fuel

  economy improvements.)

  A key assumption in the model is how consumers respond

  to the price signal introduced by the feebate. The

  model used the following elasticity assumptions

  to model the price response of consumers:

   

  • -10@ market share of 15 percent within a class 
  • -5@ market share of 10 percent between classes 
  • -1.0for overall sales 
  Some

  limitations of these assumptions are discussed below.

   

• NRCanVehicle Stock Model. This is a simple 

  representation of vehicle turnover and usage overa 15-year period. The model also incorporates the

  technology redesign schedule provided by EEA for the

  US Energy Information Administration in order to estimate

  the timing of technology investments. Outputs include

  the path of annual fuel savings and GHG emission reductions

  leading up to the fifteenth year.

4.2 BASE CASE AND ASSUMPTIONSTo

isolate the effect of the feebate, a base case is assessed.

This case is generated by the model and based on allowing

consumer and manufacturer behaviour to evolve naturally

in response to the availability of cost saving-technology

with no feebate. The base case has not been calibrated

to NRCan’s reference case and it does not incorporate

macroeconomic or demographic factors. However, in evaluating

the incremental impact of feebates, these are not major

limitations.

key assumptions that remain constant for all scenarios

are:

• Asingle fuel-efficiency cost curve for each class (providedby EEA)
• 2000minimum threshold for redesign of import vehicles 
• 20,000minimum threshold for redesign of domestic vehicles 
• Vehiclelife of 15 years 
• Averageyearly distance traveled of 23,500 km, declining 4percent per year
• 15percent adjustment of fuel consumption rating to approximateon-road conditions
• 23percent rebound effect (where decreased fuel costsinduce more driving, thus negating a portion of the

  feebate gains)

• 10percent discount rate. 

LIMITATIONS

all modeling exercises, the current one is a crude approximation

of reality designed to provide policy guidance. While

the model has limitations that we highlight below, it

is our view that the model can be used to inform policy.

Limitations include:

• Decisionbasis. In the real world, manufacturers 

  would redesign based on a number of complex considerationsand consumers would be driven by a variety of considerations

  that are not easily represented by a simple elasticity

  function. In this simulation, the model assumes that

  manufacturers redesign their vehicles to maintain

  market share and not to maximize profits. Similarly,

  societal costs may be fairly represented by consumer

  surplus changes, but it is not possible to estimate

  the share of the burden that would fall on producers

  and not be passed on to consumers.

• Airquality benefits. Important co-benefits 

  from reduced fuel consumption like improved air quality,a reduction in adverse health outcomes and the monetary

  value of those outcomes are also not modeled.

• Valuationof fuel savings. A central assumption 

  of the model is that consumers undervalue fuel savings.A key limitation is that there is no data on the extent

  to which this is true of Canadian consumers. As a

  result, we use the same assumption as Greene et al.

  (three years undiscounted) and we undertake a sensitivity

  analysis by examining the effect of assuming that

  consumers already fully value fuel savings. To the

  extent that consumers do undervalue fuel savings,

  a feebate would be justified on efficiency grounds

  alone, with carbon mitigation benefits additive.

• Consumerelasticities. These values determine 

  the extent to which consumers respond to price signals.Greene et al. used short-run elasticities, which are

  assumed to vary with make/model market shares, but

  are not estimated by manufacturer or vehicle class.

  Given the function used, classes with larger market

  shares have smaller elasticities, whereas models with

  small market shares have high elasticities (in some

  cases, unrealistically high). Furthermore, cross-price

  elasticities are not differentiated by make/model

  or class. This means that consumers diverted from

  buying a large SUV are assumed to be equally likely

  to buy a subcompact as a minivan or mid-size SUV.

  It also means that cross-price elasticities are higher

  across the board for classes with large market shares;

  this issue matters more for Canada, since the market

  shares are less evenly distributed than in the US.

  Since there is no comparable data on Canadian elasticities,

  our approach has been to use the Greene et al. elasticities

  but to halve them, as a way of approximating long-run

  responses and to mitigate some of the effects described

  above. We also undertake a sensitivity analysis by

  examining the effects of assuming the full elasticities

  prescribed by Greene et al.

• Staticdesigns. The model uses a database of 

  vehicles, which is based on 2003 models and assumesno changes in makes and models over the 15-year period.

  This is unrealistic but neutral in terms of costs.

  Furthermore the model uses a static technology cost

  curve that assumes no progress in available fuel economy

  technologies over the period—this assumption

  tends to overestimate costs. Finally, the model assumes

  that all technology investments are used to improve

  fuel economy and that weight and performance remain

  constant. (Given past experience, this tends to overestimate

  the fuel economy effectiveness of the investments.)

• Hybridand diesel technologies are not included. 

  As discussed in Section 2, hybrids and diesels areexpected to play a significant role in improving fuel

  economy. Unfortunately the current version of the

  model lacks the information necessary to include these

  options. (Our understanding is that Transport Canada

  is working to add them to the model soon.) As a result,

  the model overestimates costs and underestimates fuel

  economy gains.

• Effectson used vehicle markets are not modeled. 

  As discussed in Section 2, the used vehicle marketrepresents more than half of vehicle sales. If the

  price of certain models rises because of feebates,

  it is likely that some of the demand will be filled

  from the used vehicle market. However, the model assumes

  that consumers primarily respond by shifting purchases

  to other new vehicles. As a result, the effectiveness

  of fuel economy gains is overestimated.

• Thresholdapproach to redesign. The cost curve 

  approach does not account for economies of scale beyondthe pre-set threshold, as the thresholds are only

  set to limit the access to technology in a Canadian-only

  scenario.

• Spillovereffects of unilateral Canadian policy. 

  The model assumes that unilateral Canadian policieshave no effect on US policy. Thus any spillover effects

  that might occur are discounted. For example, should

  Canadian policies increase the potential for voluntary

  or mandatory fuel economy improvements in the US,

  the effect of this on the overall size of the market

  for redesign is not included. (As a result, costs

  are potentially overestimated and effectiveness is

  underestimated.)

• Reboundeffect. “Rebound” refers 

  to the increase in distance travelled that accompaniesreduced driving expenses (in this case, fuel savings).

  The model assumes a rebound effect of 23 percent—meaning

  23 percent of fuel savings are lost to this effect—based

  on research of past experience in the US. The potential

  future rebound effect in Canada has not been studied,

  but 23 percent almost certainly overestimates the

  effect and therefore underestimates the GHG savings.

SCENARIOS

primary purpose of the modeling is to explore the effects

of various feebate options. In this respect, the model

is primarily designed to examine the effects of varying

rate designs as opposed to implementation options, such

as approaches to revenue neutrality, phase-in periods,

or annual feebates at vehicle registration. As well,

the model is designed to use fuel consumption as the

rate basis.

our scenarios are selected to include variations on

the following options:

• Formof the function: Fully linear, $5,000 cap, or zerofeebate within 1.0 litre per 100 km of pivot (deadband)
• Rate:$250, 500, or $1000 per litre per 100 km 
• Numberof classes: single, car and truck, or 11 classes. 

secondary purpose of the modeling is to examine the

sensitivity of the results to differences in key assumptions.

In this respect, the following alternatives are considered:

• Elasticities
  • Baseassumption – represents long-run elasticities(i.e. half of the values used by Greene et al.

    presented above)

    • -5@ market share of 1.5 percent within a class 
    • -2.5@ market share of 10 percent between classes 
    • -0.5for overall sales 
  • Sensitivityanalysis for double these figures (i.e. the fullvalues used by Greene et al.).
• PolicyScope 
  • Baseassumption: feebates are implemented in Canadaonly
  • Sensitivityanalysis for Canada–US policy. 
• ConsumerPerception of Value of Fuel Savings 
  • Baseassumption: three years of undiscounted savings 
  • Sensitivityanalysis for fuel discounted valuation. 
• FuelPrice 
  • Baseassumption: C$0.90 per litre 
  • Sensitivityanalysis at C$1.20 per litre. 

alternative options and assumptions are grouped into

12 scenarios, as shown in Table 4.1.

RESULTS

Appendix

B contains detailed result for each of the scenarios.

Selected results are presented in Table 4.2.

Note that Scenario 7 could not be modeled because

of problems with the specification of the discontinuity.

4.2: Scenario Results

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